Monitoring and automatic scaling of data volumes

ABSTRACT

Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to co-pending U.S. patent application Ser.No. 12/415,958, entitled “Control Service and Relational DataManagement,” filed concurrently herewith, which is hereby incorporatedherein by reference.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyrightrights whatsoever.

BACKGROUND

As an increasing number of applications and services are being madeavailable over networks such as the Internet, an increasing number ofcontent, application, and/or service providers are turning totechnologies such as cloud computing. Cloud computing, in general, is anapproach to providing access to electronic resources through services,such as Web services, where the hardware and/or software used to supportthose services is dynamically scalable to meet the needs of the servicesat any given time. A user or customer typically will rent, lease, orotherwise pay for access to resources through the cloud, and thus doesnot have to purchase and maintain the hardware and/or software toprovide access to these resources.

The amount of resources needed by a customer can change over time. Forexample, the customer might require additional processing capacity forvarious applications, or might require additional storage capacity forcustomer data. Currently, the management of such resources is a manualprocedure, which requires a database administrator (DBA) or other suchoperator to view statistics and usage data by customer, and determinewhen to request that the customer authorize an increase or decrease inallocated capacity. When receiving a request from a customer to adjust acapacity, the DBA must determine the appropriate type of adjustment andperform the adjustment. Often, this requires taking down a data storefor the customer for a period of time necessary to make the adjustment.Further, such an approach can be reactive, in that a customer will notknow that an increase is needed until the capacity for the customer isfull or exceeded.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments in accordance with the present disclosure will bedescribed with reference to the drawings, in which:

FIG. 1 illustrates an environment in which various embodiments can beimplemented;

FIG. 2 illustrates an example separation of a control plane and a dataplane that can be used in accordance with various embodiments;

FIG. 3 illustrates an example process for analyzing performanceinformation that can be used in accordance with one embodiment;

FIG. 4 illustrates an example process for causing an action to beperformed in accordance with one embodiment;

FIG. 5 illustrates an example process for performing an action inaccordance with one embodiment; and

FIG. 6 illustrates an interface enabling a customer to set scalingparameters that can be used in accordance with one embodiment.

DETAILED DESCRIPTION

Systems and methods in accordance with various embodiments of thepresent disclosure may overcome one or more of the aforementioned andother deficiencies experienced in conventional approaches to managingaspects of data storage in an electronic environment. In particular,various embodiments provide a separate control environment, or controlplane, that can be used to monitor and/or control aspects of a dataenvironment, or data plane. The functionality of a control plane can beprovided as a set of Web services, for example, enabling the controlplane to act as a virtual database administrator (DBA). A user orcustomer can submit a request to the control plane through anexternally-visible application programming interface (API), for example,which can be analyzed to determine actions to be performed in the dataplane, such as actions that create, delete, modify, expand, or otherwisemodify a data store or data storage instance. State information can bepassed to a component of the data plane for each task necessary toperform the action, such that the control plane can manage theperformance of the tasks without having direct access into the datastores or other such components of the data plane. Once provisioned, auser can native access to the data instance(s) in the data plane, andcan simply point existing applications (such as MySQL applications) tothe domain name system (DNS) name or other location information for theparticular data instance. There is no restriction or modification ofquery models or other such functionality, as a user can continue to useapplications built on MySQL, Oracle, or other such database technology.

Systems and methods in accordance with various embodiments takeadvantage of a monitoring component in the control plane to continuallymonitor performance aspects of the data environment, such as bymonitoring host machines or data instances for a relational database orother such data storage system. The monitoring component can contacthost managers, or other such components in the data plane, to obtainperformance information such as the capacity and usage of processing,memory, storage, I/O, and other such resources. The monitoring componentcan store and/or receive historical information for the data plane, suchthat the monitoring component can do trending and/or historical analysisof the performance data. Using such an approach, the monitoringcomponent can predict future capacity and/or resource needs for acustomer, and can recommend appropriate scaling or other suchadjustments in capacity or other such aspects. In some embodiments,components of the control plane can be authorized to act on behalf ofthe customer, in order to automatically scale or allocate capacity asneeded (or predicted).

Use of such a control plane can enable a customer or DBA to betterunderstand the scalability bottlenecks of the data environment byautomatically collecting and analyzing data from the data environment,without being intrusive to the customer or other users of the dataenvironment. The control plane components also can determine anappropriate action to take, and can either recommend the action to thecustomer or perform the action on behalf of the customer.

In some embodiments, an operator or data service provider can send theappropriate metrics or other such information to a control service. Theservice can analyze the data, such as by performing a trending analysis,and determine appropriate actions to be taken. The control service thencan send a recommendation to the requesting operator, or canautomatically work with the data environment to perform any necessaryscaling or other such operations.

In some embodiments, a customer can be provided with the ability tospecify certain actions to be taken in certain circumstances. Forexample, a customer can be provided with an interface into the controlplane that allows the customer to authorize specific actions in responseto determinations or recommendations from the monitoring component (oranother such component of the control plane). For example, a customermight authorize an increase in processing capacity when the processingcapacity reaches a certain level, or is projected to reach a certainlevel within a certain time. A customer also might authorize an increasein storage capacity as needed, so as to not risk losing data. A customermight also specify to not exceed a certain price point, such that themonitoring component can work with an accounting or other such system toensure that resources are not allocated beyond a certain price limit.There can be other factors, such as maximum latency, minimumrequirements, etc., that can be considered as well, as discussedelsewhere herein.

FIG. 1 illustrates an example of an environment 100 for implementingaspects in accordance with various embodiments. As will be appreciated,although a Web-based environment is used for purposes of explanation,different environments may be used, as appropriate, to implement variousembodiments. The environment 100 shown includes both a testing ordevelopment portion (or side) and a production portion. The productionportion includes an electronic client device 102, which can include anyappropriate device operable to send and receive requests, messages, orinformation over an appropriate network 104 and convey information backto a user of the device. Examples of such client devices includepersonal computers, cell phones, handheld messaging devices, laptopcomputers, set-top boxes, personal data assistants, electronic bookreaders, and the like. The network can include any appropriate network,including an intranet, the Internet, a cellular network, a local areanetwork, or any other such network or combination thereof. Componentsused for such a system can depend at least in part upon the type ofnetwork and/or environment selected. Protocols and components forcommunicating via such a network are well known and will not bediscussed herein in detail. Communication over the network can beenabled by wired or wireless connections, and combinations thereof. Inthis example, the network includes the Internet, as the environmentincludes a Web server 106 for receiving requests and serving content inresponse thereto, although for other networks an alternative deviceserving a similar purpose could be used as would be apparent to one ofordinary skill in the art.

The illustrative environment includes at least one application server108 and a data store 110. It should be understood that there can beseveral application servers, layers, or other elements, processes, orcomponents, which may be chained or otherwise configured, which caninteract to perform tasks such as obtaining data from an appropriatedata store. As used herein the term “data store” refers to any device orcombination of devices capable of storing, accessing, and retrievingdata, which may include any combination and number of data servers,databases, data storage devices, and data storage media, in anystandard, distributed, or clustered environment. The application servercan include any appropriate hardware and software for integrating withthe data store as needed to execute aspects of one or more applicationsfor the client device, handling a majority of the data access andbusiness logic for an application. The application server providesaccess control services in cooperation with the data store, and is ableto generate content such as text, graphics, audio, and/or video to betransferred to the user, which may be served to the user by the Webserver in the form of HTML, XML, or another appropriate structuredlanguage in this example. The handling of all requests and responses, aswell as the delivery of content between the client device 102 and theapplication server 108, can be handled by the Web server. It should beunderstood that the Web and application servers are not required and aremerely example components, as structured code discussed herein can beexecuted on any appropriate device or host machine as discussedelsewhere herein. Further, the environment can be architected in such away that a test automation framework can be provided as a service towhich a user or application can subscribe. A test automation frameworkcan be provided as an implementation of any of the various testingpatterns discussed herein, although various other implementations can beused as well, as discussed or suggested herein.

The environment also includes a development and/or testing side, whichincludes a user device 118 allowing a user such as a developer, dataadministrator, or tester to access the system. The user device 118 canbe any appropriate device or machine, such as is described above withrespect to the client device 102. The environment also includes adevelopment server 120, which functions similar to the applicationserver 108 but typically runs code during development and testing beforethe code is deployed and executed on the production side and isaccessible to outside users, for example. In some embodiments, anapplication server can function as a development server, and separateproduction and testing storage may not be used.

The data store 110 can include several separate data tables, databases,or other data storage mechanisms and media for storing data relating toa particular aspect. For example, the data store illustrated includesmechanisms for storing production data 112 and user information 116,which can be used to serve content for the production side. The datastore also is shown to include a mechanism for storing testing data 114,which can be used with the user information for the testing side. Itshould be understood that there can be many other aspects that may needto be stored in the data store, such as for page image information andaccess right information, which can be stored in any of the above listedmechanisms as appropriate or in additional mechanisms in the data store110. The data store 110 is operable, through logic associated therewith,to receive instructions from the application server 108 or developmentserver 120, and obtain, update, or otherwise process data in responsethereto. In one example, a user might submit a search request for acertain type of item. In this case, the data store might access the userinformation to verify the identity of the user, and can access thecatalog detail information to obtain information about items of thattype. The information then can be returned to the user, such as in aresults listing on a Web page that the user is able to view via abrowser on the user device 102. Information for a particular item ofinterest can be viewed in a dedicated page or window of the browser.

Each server typically will include an operating system that providesexecutable program instructions for the general administration andoperation of that server, and typically will include a computer-readablemedium storing instructions that, when executed by a processor of theserver, allow the server to perform its intended functions. Suitableimplementations for the operating system and general functionality ofthe servers are known or commercially available, and are readilyimplemented by persons having ordinary skill in the art, particularly inlight of the disclosure herein.

The environment in one embodiment is a distributed computing environmentutilizing several computer systems and components that areinterconnected via communication links, using one or more computernetworks or direct connections. However, it will be appreciated by thoseof ordinary skill in the art that such a system could operate equallywell in a system having fewer or a greater number of components than areillustrated in FIG. 1. Thus, the depiction of the system 100 in FIG. 1should be taken as being illustrative in nature, and not limiting to thescope of the disclosure.

An environment such as that illustrated in FIG. 1 can be useful for aprovider such as an electronic marketplace, wherein multiple hosts mightbe used to perform tasks such as serving content, authenticating users,performing payment transactions, or performing any of a number of othersuch tasks. Some of these hosts may be configured to offer the samefunctionality, while other servers might be configured to perform atleast some different functions. The electronic environment in such casesmight include additional components and/or other arrangements, such asthose illustrated in the configuration 200 of FIG. 2, discussed indetail below.

Systems and methods in accordance with one embodiment provide arelational database service (“RDS”) that enables developers, customers,or other authorized users to easily and cost-effectively obtain andconfigure relational databases so that users can perform tasks such asstoring, processing, and querying relational data sets in a cloud. Whilethis example is discussed with respect to the Internet, Web services,and Internet-based technology, it should be understood that aspects ofthe various embodiments can be used with any appropriate servicesavailable or offered over a network in an electronic environment.Further, while the service is referred to herein as a “relationaldatabase service,” it should be understood that such a service can beused with any appropriate type of data repository or data storage in anelectronic environment. An RDS in this example includes at least one Webservice that enables users or customers to easily manage relational datasets without worrying about the administrative complexities ofdeployment, upgrades, patch management, backups, replication, failover,capacity management, scaling, and other such aspects of data management.Developers are thus freed to develop sophisticated cloud applicationswithout worrying about the complexities of managing the databaseinfrastructure.

An RDS in one embodiment provides a separate “control plane” thatincludes components (e.g., hardware and software) useful for managingaspects of the data storage. In one embodiment, a set of data managementapplication programming interfaces (APIs) or other such interfaces areprovided that allow a user or customer to make calls into the RDS toperform certain tasks relating to the data storage. The user still canuse the direct interfaces or APIs to communicate with the datarepositories, however, and can use the RDS-specific APIs of the controlplane only when necessary to manage the data storage or perform asimilar task.

FIG. 2 illustrates an example of an RDS implementation 200 that can beused in accordance with one embodiment. In this example, a computingdevice 202 for an end user is shown to be able to make calls through anetwork 206 into a control plane 208 to perform a task such as toprovision a data repository of the data plane 210. The user or anapplication 204 can access the provisioned repository directly throughan interface of a data plane 210. While an end user computing device andapplication are used for purposes of explanation, it should beunderstood that any appropriate user, application, service, device,component, or resource can access the interface(s) of the control planeand/or data plane as appropriate in the various embodiments. Further,while the components are separated into control and data “planes,” itshould be understood that this can refer to an actual or virtualseparation of at least some resources (e.g., hardware and/or software)used to provide the respective functionality.

The control plane 208 in this example is essentially a virtual layer ofhardware and software components that handles control and managementactions, such as provisioning, scaling, replication, etc. The controlplane in this embodiment includes a Web services layer 212, or tier,which can include at least one Web server, for example, along withcomputer-executable software, application servers, or other suchcomponents. The Web services layer also can include a set of APIs 232(or other such interfaces) for receiving Web services calls or requestsfrom across the network 206, which the Web services layer can parse orotherwise analyze to determine the steps or actions needed to act on orprocess the call. For example, a Web service call might be received thatincludes a request to create a data repository. In this example, the Webservices layer can parse the request to determine the type of datarepository to be created, the storage volume requested, the type ofhardware requested (if any), or other such aspects. Information for therequest can be written to an administration (“Admin”) data store 222, orother appropriate storage location or job queue, for subsequentprocessing.

A Web service layer in one embodiment includes a scalable set ofcustomer-facing servers that can provide the various control plane APIsand return the appropriate responses based on the API specifications.The Web service layer also can include at least one API service layerthat in one embodiment consists of stateless, replicated servers whichprocess the customer APIs. The Web service layer can be responsible forWeb service front end features such as authenticating customers based oncredentials, authorizing the customer, throttling customer requests tothe API servers, validating user input, and marshalling or unmarshallingrequests and responses. The API layer also can be responsible forreading and writing database configuration data to/from theadministration data store, in response to the API calls. In manyembodiments, the Web services layer will be the only externally visiblecomponent, or the only component that is visible to, and accessible by,customers of the control service. The servers of the Web services layercan be stateless and scaled horizontally as known in the art. APIservers, as well as the persistent data store, can be spread acrossmultiple data centers in a region, for example, such that the serversare resilient to single data center failures.

The control plane in this embodiment includes what is referred to hereinas a “sweeper” component 214. A sweeper component can be any appropriatecomponent operable to poll various components of the control plane orotherwise determine any tasks to be executed in response to anoutstanding request. In this example, the Web services layer might placeinstructions or information for the “create database” request in theadmin data store 222, or a similar job queue, and the sweeper canperiodically check the admin data store for outstanding jobs. Variousother approaches can be used as would be apparent to one of ordinaryskill in the art, such as the Web services layer sending a notificationto a sweeper that a job exists. The sweeper component can pick up the“create database” request, and using information for the request cansend a request, call, or other such command to a workflow component 216operable to instantiate at least one workflow for the request. Theworkflow in one embodiment is generated and maintained using a workflowservice as is discussed elsewhere herein. A workflow in general is asequence of tasks that should be executed to perform a specific job. Theworkflow is not the actual work, but an abstraction of the work thatcontrols the flow of information and execution of the work. A workflowalso can be thought of as a state machine, which can manage and returnthe state of a process at any time during execution. A workflowcomponent (or system of components) in one embodiment is operable tomanage and/or perform the hosting and executing of workflows for taskssuch as: repository creation, modification, and deletion; recovery andbackup; security group creation, deletion, and modification; usercredentials management; and key rotation and credential management. Suchworkflows can be implemented on top of a workflow service, as discussedelsewhere herein. The workflow component also can manage differencesbetween workflow steps used for different database engines, such asMySQL, as the underlying workflow service does not necessarily change.

In this example, a workflow can be instantiated using a workflowtemplate for creating a database and applying information extracted fromthe original request. For example, if the request is for a MySQL®Relational Database Management System (RDBMS) instance, as opposed to anOracle® RDBMS or other such instance, then a specific task will be addedto the workflow that is directed toward MySQL instances. The workflowcomponent also can select specific tasks related to the amount ofstorage requested, any specific hardware requirements, or other suchtasks. These tasks can be added to the workflow in an order of executionuseful for the overall job. While some tasks can be performed inparallel, other tasks rely on previous tasks to be completed first. Theworkflow component or service can include this information in theworkflow, and the tasks can be executed and information passed asneeded.

An example “create database” workflow for a customer might includestasks such as provisioning a data store instance, allocating a volume ofoff-instance persistent storage, attaching the persistent storage volumeto the data store instance, then allocating and attaching a DNS (domainname system) address or other address, port, interface, or identifierwhich the customer can use to access or otherwise connect to the datainstance. In this example, a user is provided with the DNS address andport to be used to access the instance. The workflow also can includetasks to download and install any binaries or other information used forthe specific data storage technology (e.g., MySQL). The workflowcomponent can manage the execution of these and any related tasks, orany other appropriate combination of such tasks, and can generate aresponse to the request indicating the creation of a “database” inresponse to the “create database” request, which actually corresponds toa data store instance in the data plane 210, and provide the DNS addressto be used to access the instance. A user then can access the data storeinstance directly using the DNS address and port, without having toaccess or go through the control plane 208. Various other workflowtemplates can be used to perform similar jobs, such as deleting,creating, or modifying one of more data store instances, such as toincrease storage. In some embodiments, the workflow information iswritten to storage, and at least one separate execution component (notshown) pulls or otherwise accesses or receives tasks to be executedbased upon the workflow information. For example, there might be adedicated provisioning component that executes provisioning tasks, andthis component might not be called by the workflow component, but canmonitor a task queue or can receive information for a provisioning taskin any of a number of related ways as should be apparent.

As mentioned, various embodiments can take advantage of a workflowservice that can receive requests or calls for a current state of aprocess or task, such as the provisioning of a repository, and canreturn the current state of the process. The workflow component and/orworkflow service do not make the actual calls or requests to performeach task, but instead manage the state and configuration informationfor the workflow that enables the components of the control plane todetermine the next task to be performed, and any information needed forthat task, then generate the appropriate call(s) into the data planeincluding that state information, whereby a component of the data planecan make the call to perform the task. Workflows and tasks can bescheduled in parallel in order to increase throughput and maximizeprocessing resources. As discussed, the actual performing of the taskswill occur in the data plane, but the tasks will originate from thecontrol plane. For example, the workflow component can communicate witha host manager, which can make calls into the data store. Thus, for agiven task a call could be made to the workflow service passing certainparameters, whereby the workflow service generates the sequence of tasksfor the workflow and provides the current state, such that a task forthe present state can be performed. After the task is performed (orotherwise resolved or concluded), a component such as the host managercan reply to the service, which can then provide information about thenext state in the workflow, such that the next task can be performed.Each time one of the tasks for the workflow is performed, the servicecan provide a new task to be performed until the workflow is completed.Further, multiple threads can be running in parallel for differentworkflows to accelerate the processing of the workflow.

The control plane 208 in this embodiment also includes at least onemonitoring component 218. When a data instance is created in the dataplane, information for the instance can be written to a data store inthe control plane, such as a monitoring data store 220. It should beunderstood that the monitoring data store can be a separate data store,or can be a portion of another data store such as a distinct set oftables in an Admin data store 222, or other appropriate repository. Amonitoring component can access the information in the monitoring datastore to determine active instances 234 in the data plane 210. Amonitoring component also can perform other tasks, such as collectinglog and/or event information from multiple components of the controlplane and/or data plane, such as the Web service layer, workflowcomponent, sweeper component, and various host managers. Using suchevent information, the monitoring component can expose customer-visibleevents, for purposes such as implementing customer-facing APIs. Amonitoring component can constantly monitor the health of all therunning repositories and/or instances for the control plane, detect thefailure of any of these instances, and initiate the appropriate recoveryprocess(es).

Each instance 234 in the data plane can include at least one data store226 and a host manager component 228 for the machine providing access tothe data store. A host manager in one embodiment is an application orsoftware agent executing on an instance and/or application server, suchas a Tomcat or Java application server, programmed to manage tasks suchas software deployment and data store operations, as well as monitoringa state of the data store and/or the respective instance. A host managerin one embodiment listens on a port that can only be reached from theinternal system components, and is not available to customers or otheroutside entities. In some embodiments, the host manager cannot initiateany calls into the control plane layer. A host manager can beresponsible for managing and/or performing tasks such as setting up theinstances for a new repository, including setting up logical volumes andfile systems, installing database binaries and seeds, and starting orstopping the repository. A host manager can monitor the health of thedata store, as well as monitoring the data store for error conditionssuch as I/O errors or data storage errors, and can restart the datastore if necessary. A host manager also perform and/or mange theinstallation of software patches and upgrades for the data store and/oroperating system. A host manger also can collect relevant metrics, suchas may relate to CPU, memory, and I/O usage.

The monitoring component can communicate periodically with each hostmanager 228 for monitored instances 234, such as by sending a specificrequest or by monitoring heartbeats from the host managers, to determinea status of each host. In one embodiment, the monitoring componentincludes a set of event processors (or monitoring servers) configured toissue commands to each host manager, such as to get the status of aparticular host and/or instance. If a response is not received after aspecified number of retries, then the monitoring component can determinethat there is a problem and can store information in the Admin datastore 222 or another such job queue to perform an action for theinstance, such as to verify the problem and re-provision the instance ifnecessary. The sweeper can access this information and kick off arecovery workflow for the instance to attempt to automatically recoverfrom the failure. The host manager 228 can act as a proxy for themonitoring and other components of the control plane, performing tasksfor the instances on behalf of the control plane components.Occasionally, a problem will occur with one of the instances, such asthe corresponding host, instance, or volume crashing, rebooting,restarting, etc., which cannot be solved automatically. In oneembodiment, there is a logging component (not shown) that can log theseand other customer visibility events. The logging component can includean API or other such interface such that if an instance is unavailablefor a period of time, a customer can call an appropriate “events” orsimilar API to get the information regarding the event. In some cases, arequest may be left pending when an instance fails. Since the controlplane in this embodiment is separate from the data plane, the controlplane never receives the data request and thus cannot queue the requestfor subsequent submission (although in some embodiments this informationcould be forwarded to the control plane). Thus, the control plane inthis embodiment provides information to the user regarding the failureso the user can handle the request as necessary.

As discussed, once an instance is provisioned and a user is providedwith a DNS address or other address or location, the user can sendrequests “directly” to the data plane 210 through the network using aJava Database Connectivity (JDBC) or other such client to directlyinteract with that instance 234. In one embodiment, the data plane takesthe form of (or at least includes or is part of) a computing cloudenvironment, or a set of Web services and resources that provides datastorage and access across a “cloud” or dynamic network of hardwareand/or software components. A DNS address is beneficial in such adynamic cloud environment, as instance or availability failures, forexample, can be masked by programmatically remapping a DNS address toany appropriate replacement instance for a use. A request received froma user 202 or application 204, for example, can be directed to a networkaddress translation (NAT) router 224, or other appropriate component,which can direct the request to the actual instance 234 or hostcorresponding to the DNS of the request. As discussed, such an approachallows for instances to be dynamically moved, updated, replicated, etc.,without requiring the user or application to change the DNS or otheraddress used to access the instance. As discussed, each instance 234 caninclude a host manager 228 and a data store 226, and can have at leastone backup instance or copy in persistent storage 230. Using such anapproach, once the instance has been configured through the controlplane, a user, application, service, or component can interact with theinstance directly through requests to the data plane, without having toaccess the control plane 232. For example, the user can directly issuestructured query language (SQL) or other such commands relating to thedata in the instance through the DNS address. The user would only haveto access the control plane if the user wants to perform a task such asexpanding the storage capacity of an instance. In at least oneembodiment, the functionality of the control plane 208 can be offered asat least one service by a provider that may or may not be related to aprovider of the data plane 210, but may simply be a third-party servicethat can be used to provision and manage data instances in the dataplane, and can also monitor and ensure availability of those instancesin a separate data plane 210.

As discussed, one advantage to use of a control plane is that thecontrol plane can function as a virtual database administrator (DBA) andavoid the need for a human DBA to perform tasks such as monitoringperformance data and performing trending or other such analysis. Acontrol plane can also perform functions such as automaticallyperforming scaling or other such actions in the event of an actual orpredicted need for adjustment in capacity. In conventional systems,metrics or other such information are collected and a DBA is tasked withanalyzing the information. Exceeding an allocated processing, memory, orstorage capacity in the cloud, for example, can result in a loss ofdata, resource availability, or other such failure. Conventionalapproaches relying on a DBA to perform actions such as monitoring,analysis, and adjustment are expensive and time-consuming, and canresult in significant unavailability of customer data during theadjustment process.

As discussed above, a control plane can be used to perform tasks such ascollecting data, analyzing the data, and determining appropriate actionsto be taken. FIG. 3 illustrates an example process 300 that can be usedby components of a control plane to monitor resource usage and determinewhen adjustments should be made in accordance with one embodiment. Inthis example, a monitoring component of the control plane is able toperiodically send requests for performance data into the data plane 302.As discussed above, these requests can be sent to host managers, whichare able to collect performance information from the host devices, datainstances, and other components of the data environment monitored byeach host manager. In response to a request, each corresponding hostmanager can collect the information needed to respond to the request,such as allocation, capacity, and/or usage information for componentssuch as processors (e.g., CPUs), memory (e.g., RAM), or storage (e.g.,data volume). The information can include current information and/orrecent information since the last request. Once each host manager hascollected the appropriate information, the information can be sent as aresponse that is received to the monitoring component of the controlplane 304. Upon receiving the information, the monitoring component canparse or otherwise extract the appropriate information, and analyze theextracted performance information 306. In some cases, the monitoringcomponent can determine current capacity values and compare thosecapacity values to thresholds specified by a customer or operator 308.While the term “customer” is used herein to refer to the “owner” ofdata, or a data store or instance hosted by the RDS system, it should beunderstood that the term customer is merely an example, and that anyappropriate user or developer can be allowed to access the control planeand/or data plane in the various embodiments. In some cases, themonitoring component might also (or alternatively) pull historical datafrom a monitoring data store (or other such location of the controlplane) and perform trending analysis on the data 310. For example, thecapacity values might not currently exceed a threshold, but based upon arate of increase or other such information, it can be predicted that thecapacity value will meet or exceed such a threshold at a determinedtime. Based on the analysis, the monitoring component can determinewhether any actions should be taken 312, such as a scaling of capacityfor a given customer. If no action is to be taken, the monitoringprocess can simply continue. If an action is to be taken, adetermination can be made, depending upon the embodiment, as to whetherthe control plane is authorized to perform the action 314. If thecontrol plane is authorized to act, the monitoring component can causeinformation for the determined action to be stored to a job queue 316.If the control plane is not authorized to act automatically, themonitoring component can inform the customer of the situation 318 suchthat the customer can decide to scale or perform another such action.

In some embodiments, a customer can be provided with the option ofdetermining which (if any) actions should be taken automatically, aswell as the criteria for which any of those actions should be taken. Thecriteria also can be set by a DBA, database service provider, or otherappropriate entity. Further, although a monitoring component isdescribed in this example, it should be understood that variousfunctionality can be allocated to additional and/or alternativecomponents of the control plane within the scope of the variousembodiments.

FIG. 4 illustrates in more detail an example process 400 by an actioncan be scheduled to be performed in accordance with one embodiment. Inthis example, performance information is monitored for aspect of thedata environment 402 and a determination is made that an action is (oris likely to be) needed 404, using an approach such as that describedwith respect to FIG. 3. If an action is recommended to be performedbased upon such an analysis, the monitoring component can checkinformation stored to a monitoring data store or other such locationthat stores authorization information. In some embodiments, this caninclude customer preference information, wherein a customer can selectand/or modify how different actions are authorized as discussedelsewhere herein. A determination is made as to whether the controlplane is authorized to perform and/or schedule the recommended action406. If the control plane is not authorized to automatically schedulethe action, a request or other such notification can be sent or providedto the customer, or other authorized user, requesting authorization toperform the action 408. This request can include any appropriateinformation, such as the current capacity, any predicted capacity,threshold information, and recommended action information. Adetermination is made as to whether a response is received from thecustomer within a predetermined amount of time 410, which can vary fordifferent actions, customers, embodiments, etc. If no authorization isgranted, such as may be due to no response being received or due to anexplicit instruction from the customer, then the system can simplycontinue the monitoring process without making a modification. In somecases, the system might wait a specified amount of time to determine ifan action should still be taken, and can follow up after a specifiedamount of time. In other embodiments, a secondary threshold can bespecified wherein the system will not contact the customer again unlessanother threshold is met or exceeded, such as where a resource isactually at capacity instead of simply being predicted to be at capacityat some point in the future. If the authorization is received from thecustomer, or if the control plane was authorized to perform or schedulean action, then information for the action can be stored to a job queue412 or other such location. Once information is stored to the job queue,the action can be performed 414 and the customer notified 416.

FIG. 5 illustrates an example process 500 for performing the action andnotifying the customer, in accordance with one embodiment. Usingcomponents and/or processes such as those discussed above, a determinedaction with respect to the data environment is authorized to beperformed 502. As discussed, this can take the form of the monitoringcomponent automatically requesting an action to be performed or acustomer authorizing the performance of an action, while in otherembodiments a customer could instead submit a request via anexternally-facing API of the Web services layer, which can parse therequest to determine the action(s) being requested. In this embodiment,information for the action, such as the type of action and parameters tobe used to perform the action, is written to a job queue 504, such asmay be located in an Admin data store or other such storage location.The job queue can be monitored, such as by a sweeper component, todetermine the presence of job information 506 and, when job informationis detected, a request can be sent to initiate a workflow for therequested action 508. This can include a request sent by the sweepercomponent to a workflow component and/or service to instantiate aworkflow. In other embodiments, a workflow component might monitor thejob queue for jobs, or a component of the Web services layer may sendthe job information directly to a workflow component.

Upon receiving the job information, the information is analyzed todetermine and/or assemble an appropriate workflow for the requestedaction 510. As discussed, different tasks can be selected for theworkflow based upon factors such as the type of action requested and thetype of database engine being used. Beginning with the first task of theworkflow, state information is sent to a host manager in the dataenvironment operable to use the state information to determine a task tobe performed, perform the task with respect to a data repository and/ordata instance, and return a response upon completion of the task 512.Upon receiving the response, the workflow component determines whetherthere is another task to be performed 514. If so, state information forthe next task is sent to the host manager, and upon completion of thattask the host manager sends a response to the workflow component. Afterthe final task has been completed, a message is sent to the requestingcustomer (or another appropriate user, application, or location) thatthe requested action has been completed 516. After the action has beenperformed, the customer is able to directly access the data instanceupon which the action was performed using a data interface of the dataenvironment, without accessing or passing through the control plane 518.As mentioned, the user can provided with a DNS name and port number, forexample, such that if the action resulted in movement of data or anothersimilar action, the customer or an application can continue to use thesame DNS name, which will be directed to the appropriate location in thedata plane.

There can be various aspects of the data plane that can be monitored,and different policies that can be applied to each. For example, therates at which data and CPU usage change can vary significantly from therates at which data storage vary. There also can be other aspects, suchas data input and output (I/O), that change at different rates as well.Each of these aspects can require different metrics to be captured(e.g., available bandwidth vs. storage capacity), and can requiredifferent algorithms to analyze those metrics. There also can bedifferent historical information captured and information logged, whichcan be used to determine when to scale or perform another such action.Some embodiments also require separate interfaces for each of theseactions. Such factors can make it very difficult to manage manually, andcan be advantageously provided by the control plane.

For example, a monitoring component can determine that a data store fora customer is mostly memory bound because the customer is read intensiveand thus the data environment is allocating significant effort on thebuffer cache. In such an example, the processing capacity and memory canbe the bottleneck to be addressed. If the customer is write intensive,on the other hand, then the customer can mostly be writing to disk andthe I/O might be the bottleneck. If the customer is storage bound, wherethe amount of data is increasing continually, the monitoring componentcan anticipate future need and can recommend adjustments to the customersuch as adding 20 GB (as an example) of storage capacity per month.

As discussed, the monitoring component can call into one or more hostmanagers to obtain information such as CPU and memory utilization, I/Ometrics, and storage space usage. The information to be obtained caninclude not only the current data, but also log information. Themonitoring component can analyze historical data for a period such asthe past two weeks, for example, and can run trending analysis or othertypes of data analysis. The trending analysis can be anything from alinear fit to a complex prediction algorithm as known in the art fortrending, prediction, or other such purposes. In other embodiments, thehistorical data can be exposed to the customer (or another appropriateentity) for analysis.

When information analyzed by the monitoring component is determined torequire an action, such as through an automatic authorization orcustomer authorization, information for the action in one embodiment isfed into at least one trigger mechanism. The trigger mechanism can beany appropriate component of the control plane (or external to thecontrol and data planes in some embodiments), wherein analysis of atleast one metric meeting or exceeding a threshold can result in atrigger mechanism being activated. Instead of, or in addition to,writing information to a job queue as discussed above, the triggermechanism receiving the action information can cause a workflow to bekicked off for a particular action. For example, a customer or operatorcan set up a trigger to kick off a workflow to increase processingcapacity if the processing capacity over a two week period isconsistently over 70%. Thus, when the monitoring component analyzeshistorical data for that customer, a determination that the capacity wasover 70% for at least the threshold period can cause information for thedetermination to be fed to at least one trigger mechanism, in order tokick off the appropriate workflow or otherwise cause the scaling actionto be performed as discussed or suggested herein.

A user can set several such thresholds, which can be used by themonitoring system to determine whether an action should be taken or atleast recommended. FIG. 6 illustrates an example 600 of a resourceconfiguration page that can be used to provide thresholds,authorizations, and other such information in accordance with oneembodiment. In this example, a customer is able to access a page througha browser or other user interface application to view and/or modifyauthorization settings. Although not shown, it should be understood thatthe customer can be required to go through an authentication orverification process as known in the art. In some embodiments, the useraccesses the resource configuration page through the Web services layerof the control plane, and is authorized or verified using the mechanismsprovided therein. The user can specify a group, account, or other suchidentifying information 602, as a customer can have multiple accountsfor different applications, data sources, etc. For each account, thecustomer can be presented with user-modifiable options 604 to specifyvarious resources in the data plane and criteria for modifying thoseresources. In this example, the customer has selected a processingresource, and specified that the processing allocation for this useraccount should be between 60% and 90%. A user might specify a top end of90% because, for example, the customer wants to avoid being at, orexceeding, capacity faster than an adjustment can be made. A customeralso might specify a minimum usage allocation, as the customer may notwant to pay for excessive processing capability that is not being used.The customer in this example also specified that the control plane isable to make this adjustment automatically once it is determined that anaction should be taken for the processing resource. The customer alsohas specified a threshold that the action should be taken when it ispredicted that the capacity will fall outside the specified range within30 minutes, as determined by trending or other such analysis.

In this example, the customer also has specified criteria for scalingthe storage for this account. As shown, the customer has specified thatthe storage should be at 85%-95% of capacity. The customer can use atighter range for the storage, as storage capacity will likely vary moreslowly than the processing capacity. The customer has also specifiedthat customer approval is required before scaling the storage. In thiscase, the customer has specified that the customer should be notifiedone day in advance of when the storage capacity is predicted to beoutside the specified range. The customer then can decide whether or notto adjust the storage, as well as to decide the amount of storage tore-allocate.

One advantage to providing a user with the ability to authorizeautomatic adjustments is that components of the control environment canautomatically scale various components or resources in the data plane inorder to ensure that the customer always has sufficient capacity, andcan reduce the allocated capacity when not required, in order to reducethe overall cost to the customer. Such an approach can be beneficial incloud computing environments, for example, where a customer may bepurchasing processing, memory, data, and other such capacity, but doesnot care about aspects such as the location, type, number, or otheraspects of the resources, caring instead about factors such asavailability, cost, and reliability. By enabling the system toautomatically scale the resources without affecting the availability ofthe resources, a customer can be sure to almost always have sufficientresources allocated without having to purchase an excessive amount ofresources in order to handle periods of peak capacity.

In one embodiment, metrics are automatically collected for parameterssuch as processing capacity, storage capacity, etc., as discussed above.The information can be stored to a monitoring data store or other suchlocation for analysis by the components of the control plane (or forexposure to a customer in some cases). The monitoring component (orother such component) can run trending analysis on this information overa specified period of time, and can further extrapolate the informationto predict future needs, bottlenecks, or other such circumstances. Inone embodiment standard prediction and extrapolation algorithms can beused, such as linear or non-linear algorithms known or conventionallyused for prediction and extrapolation of data. When authorized by thecustomer (either through customer settings or as part of the customersubscribing to a control service, for example), the monitoring componentcan automatically cause an action to be performed each time a bottleneckis predicted within a certain amount of time, a resource is above orbelow a threshold range for a period of time, or for any otherappropriate criteria. As part of the workflow generated for the action,a task can invoke the appropriate API to perform the desired scaling.For example, a “modifyDatabase” or similar API can be called to increaseor decrease the storage capacity for a customer.

An advantage to such an approach is that the scaling of storage caninvolve adding a data instance and rebalancing the storage, which can beperformed without taking down, or otherwise affecting the availabilityof, the customer data store. In many cases, a user will not notice achange occur. In conventional systems, a DBA would need to obtain theadditional storage and add the storage to the RAID (Redundant Array ofInexpensive Disks) controller, repurpose at least one machine, rebootthe operating system, and/or perform other such tasks which can make thedata store unavailable for a period of time. In a system in accordancewith various embodiments, however, an extra data volume can beprovisioned and attached to the data instance to increase storagecapacity. For example, if storage capacity for a customer is to beincreased by 200 GB, the service can provision four or five volumes of40 GB or 50 GB each, and attach those volumes to the instance. Theattached volumes can be added to a single logical volume, which canemulate the behavior of one single volume, disk, or other suchabstraction. Each physical volume is added to, or removed from, thelogical volume group in order to increase or decrease capacity. Once thecapacity is changed, re-balancing across the new set of volumes can beperformed automatically, with new writes or other actions automaticallypercolating to the appropriate volumes. Since a logical volume managerapproach is being used over the data instances, the data store does notneed to be taken down for any reason. Similarly, requests to arelational database instance will not fail as a result of the scalingaction.

Scaling of other resources can be performed in a similar fashion. Forexample, processor or CPU scaling can be performed automatically asneeded. In some cases, it may be necessary to make the data storetemporarily unavailable in order to adjust or scale resources such asthe processing, memory, or I/O resources. Each customer or operator canspecify a maintenance window, such as a time period of traditionally lowlevels of activity, in which such actions are to occur. Information andvarious metrics can be obtained for a resource, and when any action isdetermined to be necessary, information for the action can be written toa job queue. For actions such as the scaling of processing capacity,where it can be necessary to take down the data store for a small periodof time, the information written to the job queue can include a flag orother parameter value indicating that the action is only to be performedduring the next (or a subsequent) maintenance window. A sweeper or othersuch component checking the job queue can examine the parameter value,and only extract the job during a maintenance window. In otherembodiments, the information written to the job queue can include a timerange or other appropriate information indicating to a sweeper componentwhen to extract the information and perform the action. In still otherembodiments, a sweeper might extract the job information at any time,and as part of the task information for a workflow a time window can beincluded wherein a component of the data plane is to perform the task.Several other such approaches can be used within the scope of thevarious embodiments.

Auto-Scaling Example

In this example, a monitoring component performs trending andextrapolation of customer information from the data plane and determinesthat an increase in capacity is recommended. In this example, thecustomer has an existing volume group with one physical volume of 40 GB,and the recommended action is to add another 30 GB of storage capacity.The monitoring component can cause a workflow to be executed asdiscussed elsewhere herein. As part of the workflow, a task can cause ahost manager to initiate at least one new volume using a “/pvcreate<device_name>” or similar command or API. Here, a single volume of 30 GBis being added. Another task can instruct a host manager to extend theexisting volume group by adding the new physical volume, such as bycalling a “vgextend <VolumeGroup><device_name>” or similar command orAPI. Another task can rebalance the volume group by analyzing theallocation map for each physical volume for the particular volume groupto determine the physical extents (PEs) for each volume. Each physicalvolume is divided into chunks of data, known as physical extents, whichgenerally have the same size as the logical extents for the volumegroup. By analyzing the allocation maps for each volume, a determinationcan be made that, for this example, the first (40 GB) physical volumehas a total physical extent (PE) count of 10239, an allocated PE countof 10239, and a free PE count of 0. For the second (30 GB) physicalvolume, there is a total PE count of 7500, with an allocated PE count of0, and a free PE count of 7500. Thus, there are 17739 physical extentsacross the first and second devices, which can be distributed once thenew volume is added. The total available extents and total used extentsare determined by adding the extents for each volume in the volumegroup. In this example:Total Extents=10239+7500=17739Total Used Extents=10239+0=10239The percentage of usage of each volume can be calculated by dividing thetotal PEs for a volume by the total number of extents, and thenmultiplying this value by the total number of used extents. In thisexample:First device utilization=10239/17739*10239=5910Second device utilization=7500/17739*10239=4329The allocated space can be rebalanced to maximize the IOPS (input/outputoperations per second) performance for the volume group. In thisexample, the rebalancing can be performed by reallocating and moving PEsto the second device, such as by calling a“/pvmove/dev/second_device:5910-10239” command, which reallocates 4329PEs to the second physical volume per the calculation above. After therebalancing is completed, the logical volume and/or file system can beextended for the new capacity.

A similar process can be performed when reducing storage capacity. Atleast one volume can be removed from the volume group in order to reducethe volume group storage to the desired capacity. The total extents thencan be compared with the usage of each remaining volume to rebalanceand/or reallocate across the adjusted volume group.

For each of the tasks in such a workflow, at least one test for successor failure can be executed. For example, it can be desirable to ensurethat a volume was successfully created before adding the volume to thevolume group and attempting to reallocate PEs to that volume. If a testis run for a task, and it is determined that the task was notsuccessful, the task can be retried at least one time (possibly up to adetermined or selected number of times) before generating an errormessage or other such notification. The testing and retry can beperformed automatically via the data environment, or as managed by thecontrol environment. If a task fails a specified number of times, theentire process should be failed in order to avoid errors, data loss, orother such issues. Further, the control plane can manage the reversal ofprevious tasks, such as removing a volume from a volume group if the PEscannot be reallocated to that volume. Various other approaches can beused as well within the scope of the various embodiments.

Another service that can be provided to a potential customer is toperform and/or recommend scaling based at least in part upon factorssuch as cost and latency. For example, a customer might wish to scale asnecessary to provide optimal performance, but might not wish to scalebeyond a certain cost point. A customer also might be willing to allowlatency to reach a certain level before scaling unless a certain costbenefit is determined to be gained from the scaling. In otherembodiments, a customer might request the lowest cost configuration fora given situation. For example, a situation can arise that might beaddressed by scaling memory for purposes of caching, scaling the numberof concurrent connections, and/or by increasing the processing speed orcapacity. At least one algorithm can be used by the control plane toanalyze the cost/benefit of each such adjustment, and the permutationsof each possible adjustment, to determine a lowest cost solution to thecustomer. This could include any appropriate combination, such asscaling a portion of the recommended processing capacity in conjunctionwith scaling a portion of the recommended memory capacity, etc. Anyappropriate algorithm for analyzing metrics and cost factors todetermine an optimal solution can be used as should be apparent to oneof ordinary skill in the art in light of the teachings and suggestionscontained herein.

As discussed previously, the use of a control plane or service inaccordance with various embodiments does not restrict the type of SQLqueries that a customer can run, and does not impose any restrictionsrelating to construction of a schema, such as to be partition ready andnot allow queries spanning partitions. Instead, a repository such as arelational database can be provisioned in a computing “cloud” withoutrestricting the users' schema or queries. As commonly known, even thoughthere is a theoretical SQL standard, the SQL quirks, syntaxes and theirbehaviors (e.g., NULL handling) vary across different relationaldatabase engines (e.g., MySQL, Oracle, or Postgres). For at least thesereasons, users may wish to choose a relational database engine that isfamiliar for purposes of programming and operations. Such an approachallows customers to use the same set of database tools that thecustomers have used previously for tasks such as data modeling,development, and debugging, even when the customers migrate their datastores to the cloud (or elsewhere) via the control plane. Using such anapproach, customers are not required to rewrite their application or anyoperational tools, which lowers the barrier of entry significantly forcustomers to move data to the cloud.

A customer's data repositories can be moved to the cloud in oneembodiment by running the repositories on compute nodes of a cloudcomputing environment. Block level storage volumes, such as off-instancestorage volumes that persist independently from the life of an instance,can be used with these instances for storing the repository binary, logsand volumes, for example. Such an approach can be advantageous, as thevirtualization provides flexibility to quickly and easily scale acompute and storage resources for a repository. Further, such anapproach can provide for persistent storage in the cloud.

As known in the art, relational databases can be run in different modes,such as may include: stand-alone (non-replicated), replicated, orreplicated and partitioned. A customer typically makes the choice ofwhich mode to run for a repository based on the availability andscalability needs of the repository and the incurred total cost ofownership (TCO). Some applications and services to not require arepository to be highly available and durable, and may instead utilize astand-alone repository that is able to tolerate outages on the order ofminutes. Other applications and servers can require a repository to bealways available, and require the repository to never lose data even inthe event of a failure. In this case, the applications and servicestypically require a replicated database offering. Some users,applications, or services require a massively scalable repository thatcan partition data across multiple repositories, such that scaling canoccur beyond the compute and storage capacity of a single database. Toaddress these different use cases, an approach in accordance with oneembodiment offers at least two modes, such as stand-alone and highavailability, for each database engine. Some embodiments also allowcustomers build their own partitioning layer on top of eitherstand-alone or high availability repositories.

As mentioned, the control plane layer can take advantage, or “sit ontop,” of various basic software frameworks for performing tasks such as:implementing workflows, establishing secure communication channelsbetween the host managers of the data plane and the components of thecontrol plane, installing software on the instances of the data plane,and performing various database backup and recovery procedures.

For example, a control plane layer can take advantage of a workflowservice to manage workflows. As commonly known, a key characteristic ofany workflow engine is that the engine enables asynchronous andresumable processing. As discussed above, a workflow can be thought ofas a state machine that starts with an initial state and goes through aseries of intermediate state transitions by executing different steps ofthe workflow before reaching the end goal. This end goal can be thoughtof as the terminal state of a state machine. A workflow service offersthe ability to create workflows, and provides hooks to determine thecurrent state of a given workflow and the step(s) to next be executed.The service can store the current state of the state machine, keepingtrack of the steps which executed successfully and the steps that mustbe executed to keep the workflow moving. The service does not, ingeneral, actually execute the state transitions for us. The precisetasks of executing the tasks for a workflow will in many embodiments beperformed by the “client” components of the workflow.

As discussed above, the various embodiments can be implemented in a widevariety of operating environments, which in some cases can include oneor more user computers, computing devices, or processing devices whichcan be used to operate any of a number of applications. User or clientdevices can include any of a number of general purpose personalcomputers, such as desktop or laptop computers running a standardoperating system, as well as cellular, wireless, and handheld devicesrunning mobile software and capable of supporting a number of networkingand messaging protocols. Such a system also can include a number ofworkstations running any of a variety of commercially-availableoperating systems and other known applications for purposes such asdevelopment and database management. These devices also can includeother electronic devices, such as dummy terminals, thin-clients, gamingsystems, and other devices capable of communicating via a network.

Various aspects also can be implemented as part of at least one serviceor Web service, such as may be part of a service-oriented architecture.Services such as Web services can communicate using any appropriate typeof messaging, such as by using messages in extensible markup language(XML) format and exchanged using an appropriate protocol such as SOAP(derived from the “Simple Object Access Protocol”). Processes providedor executed by such services can be written in any appropriate language,such as the Web Services Description Language (WSDL). Using a languagesuch as WSDL allows for functionality such as the automated generationof client-side code in various SOAP frameworks.

Most embodiments utilize at least one network that would be familiar tothose skilled in the art for supporting communications using any of avariety of commercially-available protocols, such as TCP/IP, OSI, FTP,UPnP, NFS, CIFS, and AppleTalk. The network can be, for example, a localarea network, a wide-area network, a virtual private network, theInternet, an intranet, an extranet, a public switched telephone network,an infrared network, a wireless network, and any combination thereof.

In embodiments utilizing a Web server, the Web server can run any of avariety of server or mid-tier applications, including HTTP servers, FTPservers, CGI servers, data servers, Java servers, and businessapplication servers. The server(s) also may be capable of executingprograms or scripts in response requests from user devices, such as byexecuting one or more Web applications that may be implemented as one ormore scripts or programs written in any programming language, such asJava®, C, C# or C++, or any scripting language, such as Perl, Python, orTCL, as well as combinations thereof. The server(s) may also includedatabase servers, including without limitation those commerciallyavailable from Oracle®, Microsoft®, Sybase®, and IBM®.

The environment can include a variety of data stores and other memoryand storage media as discussed above. These can reside in a variety oflocations, such as on a storage medium local to (and/or resident in) oneor more of the computers or remote from any or all of the computersacross the network. In a particular set of embodiments, the informationmay reside in a storage-area network (“SAN”) familiar to those skilledin the art. Similarly, any necessary files for performing the functionsattributed to the computers, servers, or other network devices may bestored locally and/or remotely, as appropriate. Where a system includescomputerized devices, each such device can include hardware elementsthat may be electrically coupled via a bus, the elements including, forexample, at least one central processing unit (CPU), at least one inputdevice (e.g., a mouse, keyboard, controller, touch screen, or keypad),and at least one output device (e.g., a display device, printer, orspeaker). Such a system may also include one or more storage devices,such as disk drives, optical storage devices, and solid-state storagedevices such as random access memory (“RAM”) or read-only memory(“ROM”), as well as removable media devices, memory cards, flash cards,etc.

Such devices also can include a computer-readable storage media reader,a communications device (e.g., a modem, a network card (wireless orwired), an infrared communication device, etc.), and working memory asdescribed above. The computer-readable storage media reader can beconnected with, or configured to receive, a computer-readable storagemedium, representing remote, local, fixed, and/or removable storagedevices as well as storage media for temporarily and/or more permanentlycontaining, storing, transmitting, and retrieving computer-readableinformation. The system and various devices also typically will includea number of software applications, modules, services, or other elementslocated within at least one working memory device, including anoperating system and application programs, such as a client applicationor Web browser. It should be appreciated that alternate embodiments mayhave numerous variations from that described above. For example,customized hardware might also be used and/or particular elements mightbe implemented in hardware, software (including portable software, suchas applets), or both. Further, connection to other computing devicessuch as network input/output devices may be employed.

Storage media and computer readable media for containing code, orportions of code, can include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information such as computer readable instructions, data structures,program modules, or other data, including RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disk (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe a system device. Based on the disclosure and teachings providedherein, a person of ordinary skill in the art will appreciate other waysand/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the invention asset forth in the claims.

What is claimed is:
 1. A computer-implemented method of scaling storagecapacity in a data environment using a separate control environment,comprising: under control of one or more computer systems configuredwith executable instructions, obtaining performance information for alogical data volume in the data environment, the performance informationincluding at least one of storage usage information or storage capacityinformation for the logical data volume, the logical data volumecorresponding to data stored among one or more physical volumes;extracting historical information for the logical data volume, thehistorical information representing values of at least some of theperformance information over a period of time; analyzing the performanceinformation and the historical information using at least one predictionalgorithm to predict that an anticipated usage value will fall outsideof at least one specified range within at least one specified timeperiod; selecting a scaling action for adjusting a storage capacity ofthe logical data volume for the anticipated usage value to fall insidethe at least one specified range within the at least one specified timeperiod based at least in part upon determining that a cost ofimplementing the scaling action is a lowest cost among a plurality ofscaling options; determining whether authorization is granted forimplementing the scaling option based at least in part upon the cost ofimplementing the scaling option not exceeding a specified costthreshold; and executing a workflow in the separate control environmentfor adjusting the storage capacity of the logical data volume in thedata environment based at least in part upon the scaling option inresponse to determining that the authorization is granted, the storagecapacity being adjusted in the data environment by: (a) changing anumber of the one or more physical volumes that collectively provide thestorage capacity for the logical data volume without reducingavailability of the logical data volume and (b) balancing input outputperformance among the one or more physical volumes.
 2. Thecomputer-implemented method of claim 1, wherein changing the number ofthe one or more physical volumes comprises: initiating at least one newphysical volume; and extending the logical data volume by attaching theat least one new physical volume.
 3. The computer-implemented method ofclaim 1, wherein balancing the input output performance among the one ormore physical volumes is based at least in part on a number of availablephysical extents for the one or more physical volumes.
 4. Acomputer-implemented method of scaling aspects of a data environmentusing a separate control environment, comprising: under control of oneor more computer systems configured with executable instructions,obtaining performance information for at least one resource of adatabase in the data environment, the performance information includingat least one of usage information or capacity information for the atleast one resource, the at least one resource associated with a logicaldevice corresponding to one or more physical devices; extractinghistorical information for the at least one resource, the historicalinformation representing values of at least some of the performanceinformation over a period of time; analyzing the performance informationand the historical information using at least one prediction algorithmto predict that an anticipated usage value for the at least one resourcewill fall outside of at least one specified range within at least onespecified time period; selecting a scaling action, from among aplurality of scaling options, for adjusting a capacity of the at leastone resource, the capacity of the at least one resource being adjustedbased at least in part upon the anticipated usage value, the scalingaction being selected based at least in part upon a respective costcorresponding to each of the plurality of scaling actions; determiningwhether authorization is granted for the scaling option based at leastin part upon the cost corresponding to the scaling option; and executinga workflow in the separate control environment for adjusting thecapacity of the at least one resource in the data environment based atleast in part upon the scaling option in response to determining thatthe authorization is granted, the capacity being adjusted in the dataenvironment by: (a) changing a number of the one or more physicaldevices that collectively provide the capacity for the logical deviceand (b) balancing input output performance among the one or morephysical devices.
 5. The computer-implemented method of claim 4, whereinthe at least one resource includes at least one of a processingcomponent, a data storage component, a memory component, acommunications component, a network I/O (input/output) component, or adata I/O component.
 6. The computer-implemented method of claim 4,wherein executing the workflow comprises: generating a series of tasksfor adjusting the capacity; and for each of the series of tasks, passingstate information from a monitoring component in the control environmentto a host manager in the data environment, wherein the host manager isoperable to execute the task and return a response to the monitoringcomponent.
 7. The computer-implemented method of claim 6, furthercomprising: determining a success or failure of each of the series oftasks before performing any subsequent task.
 8. The computer-implementedmethod of claim 6, further comprising: when a task is determined to havefailed, retrying the task at least once and determining success orfailure of each retry; and when the task and the retry are determined tohave failed, failing the workflow.
 9. The computer-implemented method ofclaim 8, wherein: failing the workflow includes rolling back eachpreviously-executed task of the workflow.
 10. The computer-implementedmethod of claim 4 further comprising: when adjusting the capacity of theat least one resource is determined not to be authorized, contacting auser for the authorization before executing the workflow.
 11. Thecomputer-implemented method of claim 4 further comprising: enabling auser to provide different levels of authorization for the at least oneresource.
 12. The computer-implemented method of claim 4, furthercomprising, after predicting the anticipated usage value for the atleast one resource: sending information including the anticipated usagevalue to an authorized user of the at least one resource; and enablingthe authorized user to call into the control environment to request theadjusting of the capacity of the at least one resource.
 13. Thecomputer-implemented method of claim 4, wherein the scaling actioncorresponds to a lowest cost among the plurality of scaling actions. 14.A system for scaling aspects of a data environment using a separatecontrol environment, comprising: at least one hardware processor; andhardware memory including instructions that, when executed by the atleast one processor, cause the system to: obtain performance informationfor at least one resource of a database in the data environment, theperformance information including at least one of usage information orcapacity information for the at least one resource, the at least oneresource including a logical device volume corresponding to one or morephysical devices; extract historical information for the at least oneresource, the historical information representing values of at leastsome of the performance information over a period of time; analyze theperformance information and the historical information using at leastone prediction algorithm to predict that an anticipated usage value forthe at least one resource will fall outside of at least one specifiedrange within at least one specified time period; select a scalingaction, from among a plurality of scaling options, for adjustment of acapacity of the at least one resource, the adjustment being based atleast in part upon the anticipated usage value, selection of the scalingaction being based at least in part upon a respective cost correspondingto each of the plurality of scaling actions; determine whetherauthorization is granted for the scaling option based at least in partupon the cost corresponding to the scaling option; and execute aworkflow in the separate control environment for the adjustment of thecapacity of the at least one resource in the data environment based atleast in part upon the scaling option in response to a determinationthat the authorization is granted, the adjustment including (a) achanging of a number of the one or more physical devices thatcollectively provide the capacity for the logical device and (b) abalancing of input output performance among the one or more physicaldevices.
 15. The system of claim 14, wherein: the at least one resourceincludes at least one of a processing component, a data storagecomponent, a memory component, a communications component, a network I/Ocomponent, or a data I/O component.
 16. The system of claim 14, whereinthe memory further includes instructions that, when executed by theprocessor, cause the system to: when the determination is that theauthorization is not granted, contact a user for the authorizationbefore executing the workflow.
 17. The system of claim 14, wherein thememory further includes instructions that, when executed by theprocessor, cause the system to: enable a user to provide differentlevels of authorization for the at least one resource.
 18. The system ofclaim 14, wherein the memory further includes instructions that, whenexecuted by the processor, cause the system to: send informationincluding the anticipated usage value to an authorized user of the atleast one resource; and enable the authorized user to call into thecontrol environment to request for the adjustment of the capacity of theat least one resource.
 19. A computer program product embedded in anon-transitory computer-readable storage medium and includinginstructions that, when executed by at least one computing device, causethe at least one computing device to: obtain performance information forat least one resource of a database in a data environment, theperformance information including at least one of usage information orcapacity information for the at least one resource, the at least oneresource including a logical device corresponding to one or morephysical devices; extract historical information for the at least oneresource, the historical information representing values of at leastsome of the performance information over a period of time; analyze theperformance information and the historical information using at leastone prediction algorithm to predict that an anticipated usage value forthe at least one resource will fall outside of at least one specifiedrange within at least one specified time period; select a scalingaction, from among a plurality of scaling options, for adjustment of acapacity of the at least one resource, the adjustment being based atleast in part upon the anticipated usage value, selection of the scalingaction being based at least in part upon a respective cost correspondingto each of the plurality of scaling actions; determine whetherauthorization is granted for the scaling option based at least in partupon the cost corresponding to the scaling option; and execute aworkflow in a control environment for the adjustment of the capacity ofthe at least one resource in the data environment based at least in partupon the scaling option in response to a determination that theauthorization is granted, the adjustment including: (a) a changing of anumber of the one or more physical devices that collectively provide thecapacity for the logical device and (b) a balancing of input outputperformance among the one or more physical devices.
 20. The computerprogram product embedded in the non-transitory storage medium of claim19, wherein: the at least one resource includes at least one of aprocessing component, a data storage component, a memory component, acommunications component, a network I/O component, or a data I/Ocomponent.
 21. The computer program product embedded in thenon-transitory storage medium of claim 19, further includinginstructions that, when executed by at least one computing device, causethe at least one computing device to: when the determination is that theauthorization is not granted, contact a user for the authorizationbefore executing the workflow.
 22. The computer program product embeddedin the non-transitory storage medium of claim 19, further includinginstructions that, when executed by at least one computing device, causethe at least one computing device to: enable a user to provide differentlevels of authorization for the at least one resource.
 23. The computerprogram product embedded in the non-transitory storage medium of claim19, further including instructions that, when executed by at least onecomputing device, cause the at least one computing device to: sendinformation including the anticipated usage value to an authorized userof the at least one resource; and enable the authorized user to callinto the control environment to request for the adjustment of thecapacity of the at least one resource.